Intelligent Reflections for Seamless V2V: Mitigating Rician Fading Effects with RIS
The innovations in Vehicle-to-Vehicle (V2V) communication have brought about a paradigm shift in intelligent transportation systems, ushering in an epoch of safety, convenience, and connectedness. V2V networks enable direct vehicle-to-vehicle communication leading to efficient traffic management, reduced accidents, and supporting advanced vehicular applications. However, this poses a significant challenge for reliable communication due to the very dynamic nature of the vehicular environments. The mobilityinduced channel variations and fading phenomena such as Rician fading cause erratic signal quality, especially within Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) situations. Reconfigurable Intelligent Surfaces (RISs) are a disruptive technology that can flexibly change how wireless communication works by reconfiguring the radio propagation environment. Using artificial surfaces that reflect, and control electromagnetic waves smartly has the potential to counteract signal degradation and enhance communications. To circumvent the inherent difficulties experienced by vehicular networks, this paper examines how RIS can be integrated into V2V communication systems under any fading condition. The paper shows a real-time scenario where two cars interact with RIS while moving at given speeds. This research investigates the impact of RIS on major performance metrics like path loss, received signal power, and channel impulse response. Finally, extensive computer simulations demonstrate that RIS mitigates fading effects, improves signal quality, and supports reliable communication in harsh weather conditions for a V2V network.
Authors
- Shripad Hebbar (ORCID: https://orcid.org/0000-0001-6826-7017)
- Praveen Kumar (ORCID: https://orcid.org/0000-0003-4820-3088)
- G. D. Goutham Simha (ORCID: https://orcid.org/0000-0002-3908-3566)
Institutions
- Manipal Academy of Higher Education (IN)
Publication Details
- Published
- 2025-03-21
- DOI
- https://doi.org/10.1109/icsses64899.2025.11009409
- Primary Topic
- Advanced Data and IoT Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00